A system and method for monitoring resuscitation and respiratory mechanics of a patient is provided. A pressure sensor detects air pressure within an air-flow path of a resuscitator and generates a first detection signal in response thereto. A flow-rate sensor detects the flow-rate within the air-flow path and generates a second detection signal In response thereto. A processor receives and processes the first and second detection signals using an algorithm to identify a ventilation rate, a lung pressure, and an air volume corresponding to the respiratory air. A report is generated of real-time feedback about respiration of the patient that includes the ventilation rate, lung pressure, and air volume.
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8. A method for monitoring resuscitation performance of a model or a patient coupled to a resuscitation device, the method comprising the steps of:
detecting an air pressure and a flow-rate of respiratory air moving through an air-flow path within a housing having an inlet and an outlet using at least one of a pressure sensor and a flow-rate sensor positioned in the housing;
generating a first detection signal indicating detected air pressure and a second detection signal indicating the flow-rate;
processing the first detection signal and the second detection signal over time using a non-linear model of lung compliance that relates the air pressure to an air volume to identify at least one of a lung pressure and the air volume
based on values of the first detection signal and the second detection signal generated only during one of an inhale or an exhale,
processing the first detection signal with respect to a first threshold value;
processing the second detection signal with respect to a second threshold value; and
communicating, using a feedback device comprising a plurality of indicators, a relative resuscitation performance in real-time based on at least one of a ventilation rate, the lung pressure, and the air volume,
the plurality of indicators indicating that there is an air leak in the air-flow path when the first detection signal is below the first threshold and the second detection signal is above the second threshold,
the plurality of indicators indicating that an airway of the model or patient is blocked when the first detection signal is above the first threshold and the second detection signal is below the second threshold,
the plurality of indicators indicating that the device is inactive or in a low-power sleep mode when the first detection signal is below the first threshold and the second detection signal is below the second threshold, and
the plurality of indicators indicating that the device is being used properly and effective resuscitation is being provided when the first detection signal is above the first threshold and the second detection signal is above the second threshold.
12. A retrofit device adapted for a resuscitator to monitor respiration of a model or a patient, the retrofit device comprising:
a housing configured to be positioned between an inlet and an outlet of a resuscitator to have an air-flow path extend therethrough;
a pressure sensor supported by the housing and configured to detect air pressure within the air-flow path of the resuscitator and generate a first detection signal in response thereto;
a flow-rate sensor supported by the housing and configured to detect flow-rate within the air-flow path and generate a second detection signal in response thereto;
a processor configured to receive and process the first detection signal and the second detection signal using a non-linear model of lung compliance that relates the air pressure to an air volume to identify at least one of a lung pressure and the air volume corresponding to the respiratory air,
the processor further configured to, based on values of the first detection signal and the second detection signal generated only during one of an inhale or an exhale:
process the first detection signal with respect to a first threshold value, and
process the second detection signal with respect to a second threshold value; and
a feedback device comprising a plurality of indicators, the feedback device being coupled to the processor,
the plurality of indicators being configured to indicate that there is an air leak in the air-flow path when the first detection signal is below the first threshold and the second detection signal is above the second threshold,
the plurality of indicators being configured to indicate that an airway of the model or patient is blocked when the first detection signal is above the first threshold and the second detection signal is below the second threshold,
the plurality of indicators being configured to indicate that the device is inactive or in a low-power sleep mode when the first detection signal is below the first threshold and the second detection signal is below the second threshold, and
the plurality of indicators being configured to indicate that the device is being used properly and effective resuscitation is being provided when the first detection signal is above the first threshold and the second detection signal is above the second threshold.
1. A device for monitoring respiration and resuscitation of a model or a patient, the device comprising:
a housing having an inlet and an outlet configured to communicate respiratory air and connected by an air-flow path;
a pressure sensor configured to detect air pressure within the air-flow path and generate a first detection signal in response thereto;
a flow-rate sensor configured to detect flow-rate within the air-flow path and generate a second detection signal in response thereto;
a processor configured to receive and process the first detection signal and the second detection signal over time using a non-linear model of lung compliance that relates the air pressure to an air volume to identify at least one of a lung pressure and the air volume corresponding to the respiratory air,
the processor further configured to, based on values of the first detection signal and the second detection signal generated only during one of an inhale or an exhale:
process the first detection signal with respect to a first threshold value, and
process the second detection signal with respect to a second threshold value; and
a feedback device comprising a plurality of indicators, the feedback device being coupled to the processor and configured to generate a report of real-time feedback about respiration of the model or patient including at least one of a ventilation rate, the lung pressure, the air volume, the blocked airway, and the air leak,
the plurality of indicators being configured to indicate that there is an air leak in the air-flow path when the first detection signal is below the first threshold and the second detection signal is above the second threshold,
the plurality of indicators being configured to indicate that an airway of the model or patient is blocked when the first detection signal is above the first threshold and the second detection signal is below the second threshold,
the plurality of indicators being configured to indicate that the device is inactive or in a low-power sleep mode when the first detection signal is below the first threshold and the second detection signal is below the second threshold, and
the plurality of indicators being configured to indicate that the device is being used properly and effective resuscitation is being provided when the first detection signal is above the first threshold and the second detection signal is above the second threshold.
13. A training device for providing feedback about respiratory air of a model or a patient during resuscitation, the training device comprising:
a pressure sensor configured to detect air pressure within an air-flow path of the training device and generate a first feedback signal in response thereto;
a flow-rate sensor configured to detect flow-rate within the air-flow path and generate a second feedback signal in response thereto;
a processor configured to receive and process the first feedback signal and the second feedback signal using a non-linear model of lung compliance that relates the air pressure to an air volume to identify at least one of a lung pressure and the air volume corresponding to the respiratory air,
the processor further configured to, based on values of the first detection signal and the second detection signal generated only during one of an inhale or an exhale:
process the first detection signal with respect to a first threshold value, and
process the second detection signal with respect to a second threshold value; and
a user interface comprising a plurality of indicators, the user interface being coupled to the processor and configured to generate a report of at least one of real-time data and pre-acquired data about respiration of the model or patient through the training device including at least one of a ventilation rate, the lung pressure, and the air volume, wherein the at least one of real-time data and pre-acquired data is compared to a resuscitation training information,
the plurality of indicators being configured to indicate that there is an air leak in the air-flow path when the first detection signal is below the first threshold and the second detection signal is above the second threshold,
the plurality of indicators being configured to indicate that an airway of the model or patient is blocked when the first detection signal is above the first threshold and the second detection signal is below the second threshold,
the plurality of indicators being configured to indicate that the device is inactive or in a low-power sleep mode when the first detection signal is below the first threshold and the second detection signal is below the second threshold, and
the plurality of indicators being configured to indicate that the device is being used properly and effective resuscitation is being provided when the first detection signal is above the first threshold and the second detection signal is above the second threshold.
2. The device as recited in
3. The device as recited in
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14. The training device as recited in
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This application represents the national stage entry of PCT International Application No. PCT/US2013/070745 filed Nov. 19, 2013, which claims the benefit of U.S. Provisional Patent Application No. 61/728,211 filed on Nov. 19, 2012, the disclosures of which are incorporated by reference here in their entirety for all purposes.
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The present invention relates to systems and methods for monitoring resuscitation or respiratory mechanics of a patient or users. More particularly, the invention relates to systems and methods for identifying ventilation rate, lung pressure, and air volume of respiratory air. In addition a constitutive non-linear model of lung compliance may be employed.
A bag-valve-mask (BVM) resuscitator is a device used to deliver air to the lungs of an incapacitated patient, with the intention of providing life support. Conventional bag-valve-mask resuscitators include a compressible air bag that forces air out of an outlet port when squeezed, and accepts air in from an inlet port when released. Bag-valve-mask resuscitators may also include a one-way valve that permits air to pass from the bag towards the patient, and inhibits exhaled air from re-entering the bag. A conformable mask is pressed tightly against the patient's face around the mouth and nose to form an airtight seal and force the air into the respiratory tract. Several different sized masks are often used interchangeably, with the appropriate mask selected depending on the age and size of the patient. Alternatively, a BVM may be coupled to endotracheal or laryngeal tube rather than a face mask. Bag-valve-mask resuscitators are often equipped with an over-pressure safety regulator, and features for optionally connecting filters or oxygen supply lines.
While standard bag-valve-mask resuscitators can be used to provide effective life support, proper use is far from guaranteed. Data shows that even the most expertly-trained practitioners may fail to operate the device correctly approximately 20 percent of the time. A common mistake in bag-valve-mask resuscitator use is allowing air leaks by failing to seal the mask properly against the patient's face. Other common mistakes that result in ineffective resuscitation include blocked airways, incorrect ventilation frequency, and insufficient lung inflation.
Each of these common mistakes can result in death or brain damage to the patient. Recent data show that of the 6.9 million children under the age of 5 who die annually, more than 43 percent die in the first month of life. Breathing problems at the time of birth (i.e., asphyxia) account for a major portion of these deaths globally. Approximately 6 million babies born annually would avoid death or severe neurologic disability if provided effective breathing assistance i.e., ventilation) within one minute of birth.
Therefore, there is a need for systems and methods to improve the quality and effectiveness of resuscitation efforts in a time sensitive manner.
The present invention overcomes the aforementioned drawbacks by providing a system and method that incorporates a pressure sensor and flow-rate sensor into a resuscitator. In particular, the present invention can determine the ventilation rate, lung pressure, and air volume of respiratory air using an algorithm that relates the air pressure and air volume in terms of elasticity and provides real-time feedback about resuscitation quality and respiration of the patient in both clinical and training applications.
In accordance with one aspect of the invention, a device for monitoring respiration and resuscitation of a patient is disclosed. The device includes a housing having an inlet and an outlet configured to communicate respiratory air and connected by an air-flow path. The device also includes a pressure sensor configured to detect air pressure within the air-flow path and generate a first detection signal in response thereto. A flow-rate sensor is configured to detect flow-rate within the air-flow path and generate a second detection signal in response thereto. Further, a processor is configured to receive and process the first detection signal and the second detection signal using an algorithm to identify at least one of a ventilation rate, a lung pressure, or an air volume corresponding to the respiratory air. A feedback device is coupled to the processor and configured to generate a report of real-time feedback about respiration of the patient through the device including at least one of ventilation rate, lung pressure, or air volume.
In accordance with another aspect of the invention, a method for monitoring resuscitation performance of a patient coupled to a resuscitation device is disclosed. The method includes detecting an air pressure and a flow-rate of respiratory air moving through an air-flow path within a housing. The housing includes an inlet and an outlet having at least one of a pressure sensor or a flow-rate sensor positioned in the housing. A first detection signal is generated that indicates detected air pressure and a second detection signal is generated that indicates the flow-rate. The first detection signal and the second detection signal are processed using a non-linear model of lung compliance that relates the air pressure to the air volume in terms of elasticity to identify at least one of a ventilation rate, a lung pressure, or an air volume. A relative resuscitation performance is communicated in real-time based on the at least one of the ventilation rate, lung pressure, or air volume.
In accordance with another aspect of the invention, a retrofit device adapted for a resuscitator to monitor respiration of a patient is disclosed. The retrofit device includes a housing configured to be positioned between an inlet and an outlet of a resuscitator to have an air-flow path extend therethrough. The retrofit device also includes a pressure sensor supported by the housing and configured to detect air pressure within the air-flow path of the resuscitator and generate a first detection signal in response thereto. A flow-rate sensor is supported by the housing and configured to detect flow-rate within the air-flow path and generate a second detection signal in response thereto. In addition, a processor is configured to receive and process the first detection signal and the second detection signal using an algorithm to identify at least one of a ventilation rate, a lung pressure, or an air volume corresponding to respiratory air.
In accordance with another aspect of the invention, a training device for providing feedback about respiratory air of a patient during resuscitation is disclosed. The training device includes a pressure sensor configured to detect air pressure within an air-flow path of the training device and generate a first feedback signal in response thereto. A flow-rate sensor is configured to detect flow-rate within the air-flow path and generate a second feedback signal in response thereto. Further, a processor is configured to receive and process the first feedback signal and the second feedback signal using an algorithm to identify at least one of a ventilation rate, a lung pressure, or an air volume corresponding to the respiratory air. A user interface is coupled to the processor and configured to generate a report of real-time data or pre-acquired data about respiration of the patient through the training device including the at least one of the ventilation rate, lung pressure, or air volume. The real-time data or the pre-acquired data is then compared to resuscitation training information.
The foregoing and other aspects and advantages of the invention will appear from the following description. In the description, reference is made to the accompanying drawings which form a part hereof, and in which there is shown by way of illustration a preferred embodiment of the invention. Such embodiment does not necessarily represent the full scope of the invention, however, and reference is made therefore to the claims and herein for interpreting the scope of the invention.
Referring particularly now to
The sensor system 26 may include a variety of components, as will be described. For example, the sensor system 26 may include a pressure sensor 27 to detect air pressure within the air-flow path 22. Also, the sensor system 26 may include a flow-rate sensor 28 disposed in the air-flow path 22 to detect flow-rate within the air-flow path 22. These and any other components, such as will be described, may be integrated within a housing 29 of the sensor system 26.
Referring now to
As shown in
Referring now to
As shown in
In operation, the air pressure and flow-rate detected by the pressure sensor 27 and the flow-rate sensor 28 may generate detection signals. For example, the signals may be generated on a continuous or discrete basis and communicated to a processor 30. The processor 30 may be configured to determine resuscitation quality in terms of a ventilation rate, a lung pressure, and an air volume using an algorithm. A display 32, for example, such as a liquid crystal display (LCD), light emitting diode (LED) display, an electronic paper display (e.g., E-Ink) or other display including colored lights, discrete sounds, or the like, may be coupled to the processor 30 to communicate a report 34 to the user. The report 34 may include real-time feedback about respiration of the patient, either inhaled or exhaled, through the resuscitation device 10. The report 34 and any of the detected signals may be stored to a memory 36 for later analysis and reporting, for example.
The pressure sensor 27 may be, for example, a capacitive pressure sensor, a hall effect sensor, a photo-diode emitter and receiver configuration, a differential pressure sensor, a strain-based sensor, a custom sensor, or a flexible diaphragm instrumented by capacitive or inductive means. The pressure sensor 27 may be configured to measure absolute pressure, gauge pressure of the respiratory air in the air-flow path 22 relative to atmospheric pressure, or differential pressure between both sides of the one-way valve 25 within the housing 14. In a non-limiting example, as shown in
Returning now to
Positioning of the pressure sensor 27 and the flow-rate sensor 28 within the housing 14 of the resuscitation device 10 may vary. As shown in
For example,
The above-described alerts provide real-time feedback to the user and may be, for example, a visual alert, an audible alert, a vibratory alert, or a combination there of. The alerts may notify the user of improper use of the resuscitation device during an actual resuscitation, for example, thereby prompting the user to provide immediate corrective action. As shown in
Referring now to
The graph shown in
Thus, the resuscitation device may provide different feedback parameters to the user depending on different training or use scenarios, such as different life support techniques. For example, a resuscitation trainer may receive data related to the air pressure, flow-rate and wave forms from the resuscitation device in order to coach users in real-time, or data related to the air pressure, flow-rate, and wave forms may be stored to the memory and reviewed for more summary training improvements, for example. Alternatively, for a resuscitation trainee or real-time user of the resuscitation device, the data (i.e., ventilation rates, lung pressures, air volumes, etc.) may be displayed within or outside of acceptable ranges, as previously described. Alternatively, standardized queries with thresholds of acceptable parameters of ventilation rates, lung pressures, air volumes, etc., may be utilized for resuscitation examinations or certifications. These thresholds may be deemed to have been sufficiently met by either reaching each, reaching each simultaneously, or by meeting an absolute or percentage time within an acceptable range.
The above-described resuscitation devices 10, 610, and 710 may be used on models or manikins as a training device, for example, or on patients such as neonates, infants, pediatrics, adults, and animals. The real-time feedback from the resuscitation device may be advantageous for users such as emergency medical technicians (EMTs), paramedics, physicians assistants, nurse practitioners, doctors, nurses, midwives, and birth-attendants for diagnosis of chronic obstructive pulmonary disease (COPD), asthma, bronchitis, pneumonia, surfactant deficiency, airway compromise, and supra-pulmonary airway obstruction, for example. Other non-medical users, such as singers, athletic trainers, and athletes may benefit from the real-time feedback of the resuscitation device used not for resuscitation but rather to measure lung mechanics.
In the case of medical uses, for example, the resuscitation device may be larger for pediatrics and adults compared to the resuscitation device used for infants or neonates. The resuscitation device for pediatric and adults may include added features of more accurate volume calculation utilizing either hardware bags external to the patient, user, or inflatable objects. Displacement and stretch sensors may be attached to the device, such as to the air bag 12, as well as user “exit” sensors configured to calculate air pressure, flow-rate and air volume. In essence, the device may be viewed as turning the resuscitation device 10 of
Referring now to
To start the process, the air pressure and flow-rate of respiratory air moving through the air-flow path within the housing is detected at process block 502. The air pressure and flow-rate are detected using the pressure sensor and flow-rate sensor positioned within the housing as described above. At process blocks 504 a first detection signal is generated indicating the detected air pressure from process block 502. Similarly, at process block 506 a second detection signal is generated indicating the detected flow-rate from process block 502. The processor 30, as shown in
Where CL is lung tissue compliance, VL is lung volume, Ppl is pressure in pleural space, and Palv is pressure in the alveoli.
Where GL is airway conductance, VL is lung volume, Pao is pressure in the airway outlet, and Palv is pressure in the alveoli.
PL=EL(VL−V0)+R*V
Where PL is the transpulmonary pressure which is the sum of airway resistive pressure and pulmonary elastic pressure. EL is the lung elastance (i.e., 1/CL), and RL is the pulmonary resistance (i.e., 1/GL).
The algorithms used to process the first detection signal and the second detection at process block 508 may be, for example, a non-linear model of lung compliance that relates the air pressure and the air volume in terms of elasticity. Using the above described algorithms, the ventilation rate, lung pressure, and air pressure of the respiratory air of the patient may be identified at process block 510. The values of the ventilation rate, lung pressure, and air pressure may then be communicated in terms of relative resuscitation performance in real-time to the user at process block 512 and shown, for example, on the display 32 to the user, as shown in
Whether the trainee, for example, or the processor analyzes the displayed values of ventilation rate, lung pressure, and air pressure at process block 514, the values can be used to determine a potential blocked airway of the patient, a wrong rate of ventilation or an air leak caused by a break in the seal between the patient and the ventilation mask, for example, at process block 516. If a blocked airway, wrong ventilation rate, an air leak, or combination thereof is detected at process block 516, an alert is communicated to the user at process block 518. As previously described, the alert may be a visual alert, a vibratory alert, or an audible alert to communicate to the user that corrective action may be necessary to provide effective resuscitation. If no airway blockage or air leak is detected at process block 516, the user may determine if the patient has been successfully resuscitated at process block 520. If the patient has not been successfully resuscitated, the resuscitation device continues to detect the air pressure and flow-rate of respiratory air at process block 502 to ensure effective resuscitation is being performed, and the same process continues until the patient is successfully resuscitated. If the patient is successfully resuscitated at process block 520, then the process may end.
Optionally, at process block 522 the first and second detection signal generated at process blocks 504 and 506, respectively, may be stored to the memory 36, as shown in
Using the resuscitation device previously described may improve the speed and effectiveness of health worker training or re-training. With real-time guidance on their performance, trainees can more quickly hone their resuscitation skills. The resuscitation device provides real-time feedback during actual resuscitation when conditions could be different and more stressful than training. In addition, real-time feedback on the quality of ventilation facilitates immediate corrective action, possibly resulting in a greater number of lives saved or morbidity avoided. Further, audit data on ventilation proficiency allows trainers to identify persistent gaps in a trainee's resuscitation techniques, and more effectively target retraining and quality improvement measures.
The present invention has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.
Mielcarz, Craig, Cedrone, Kevin, Santorino, Data, Olson, Kristian
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